4 ms·

Last year we were months from a quantum computer. The year before that we were all doing to be on the blockchain. The year before that everything was moving t

Last year we were months from a quantum computer. The year before that we were all doing to be on the blockchain. The year before that everything was moving to VR and the Metaverse. This year it's AI.

toss1 3y ago
Yup, the AI Extinction meme is both a distraction from real harms and an effort to provoke regulations to create a moat for the big players (see famous Google memo "We Have No Moat, And Neither Does OpenAI"[0]). Most importantly, while the results of the new generative LLMs and image-processing "AIs" are impressive and sometimes useful, they are nowhere near intelligent, and have only a passing resemblance to reality. There is zero ability to actually abstract and wield concepts, nevermind conceive of and seek a goal. Fun-house mirrors of human input are not any kind of existential threat to humanity or to life on earth. However the distortions they create can amplify certain human actions, particularly disruptive actions, and distracting from managing those harms is a problem. [0] https://www.semianalysis.com/p/google-we-have-no-moat-and-neither https://www.semianalysis.com/p/google-we-have-no-moat-and-ne...
- gmerc 3y ago
  While I’m sharing your assessment of the motivation I do not think it’s great to take a snapshot in time on an exponential curve and argue ‘it’s far away from being intelligent’ When something goes from not being able to do something to almost human level, arguing that almost isn’t a threat is not exactly wise.
  - LatteLazy 3y ago
    Of course a (flat) linear line looks very similar to an exponential early in on the curve... But I suppose that cuts both ways :)
  - toss1 3y ago
    >>When something goes from not being able to do something to almost human level Point taken, and yes I have read Bostron's book and others, so I understand the runaway concern. However, the issue I have is with the "almost human level". We must look at the mechanics of what is happening. The technologies of mirrors, lenses, or photography have been able for centuries to create images at far beyond the level of most humans. Yet, capturing the vectors of incident photons is in no way reproducing human capability. These "AI" tools are capturing and reproducing the vectors of existing human output of words and/or images. The output can be impressive in both the parlor game and useful senses. Yet, there is deeply no "there" there. Just look at the "single banana problem", or the massive confident hallucination problems. Consider the responses of taking a Polaroid instant-photo camera to a pre-industrial society with sophisticated artistic capabilities. They'd at first regard the camera/printer with astonishment and consider that it may have artificially human capabilities. But they'd soon figure out that the camera has no concept of a person, and cannot compose one image of two people present only at different times. We are very much like that society regarding the camera-printer, and we're still in the astonished "Holy Cowabunga!" moment. But, the more I use it, the more I'm convinced that this is, like a camera in many situations, an occasionally extremely useful tool, but nowhere near any level of actual intelligence.
- rafaelero 3y ago
  > Most importantly, while the results of the new generative LLMs and image-processing "AIs" are impressive and sometimes useful, they are nowhere near intelligent, and have only a passing resemblance to reality. There is zero ability to actually abstract and wield concepts, nevermind conceive of and seek a goal. Fun-house mirrors of human input are not any kind of existential threat to humanity or to life on earth. I am no doomer but such position is utterly ignorant. GPT-4 can do plenty of complex cognitive tasks; hell, it can even do regression if you give it a bunch of data. If you think that's not intelligence then I don't think we humans are intelligent either.
  - toss1 3y ago
    The question is HOW is it appearing to do regression or other math? Is it abstracting the meaning and context from the data and then performing an analysis, or just spitting out something resembling other training data it has seen after something resembling your prompts? This is easy to demonstrate with simple arithmetic. Ask ChatGPT4 what is 5 times 7? ChatGPT The product of 5 multiplied by 7 is 35. Now ask it what is 19748312 times 12347123? ChatGPT The product of 19,748,312 multiplied by 12,347,123 is 243,602,945,733,776. This is wrong; it is 243,834,837,306,376 The LLM has zero understanding of the problem, and it is not doing the math; it merely reflects back at us the closest vectors in the training set. It is no more doing your regression problems than it is doing the math here. And no, I cannot do that multiplication in my head either, but I can understand the terms, and either do the longhand arithmetic or put it into a calculator. Similarly, the human who knows how to do the regression UNDERSTANDS THE PROBLEM and applies a calculation method. The bullshitting human just spits back a plausible answer, which is what you are seeing from your LLM. What is ignorant is mistaking a parlor game, admittedly very sophisticated and often useful, for intelligence. And I do find it quite useful myself, but I do not mistake the output for something it is not. Edit: fix the asterisk times sign interpreted as formatting
    - DirkH 3y ago
      I'm not convinced human intellect isn't doing a similar thing with math when we are doing it fast. When I solve an arithmetic thing in my head I actually am not understanding or going by "the steps." I've just seen it so many times I have a kind of "sixth sense" so to speak. I.e. I'm kinda just pattern matching in the vector space of my memories. When I do this am I no longer using my intelligence? When we do math mistakes it is a form of hallucination just like for the LLM. In such instances you can ask a human to show their work and go step-by-step in which case they are less likely to "hallucinate." Do the same with an LLM and likewise you'll get a better answer as expected. In your example though it is true you're unlikely to get a LLM to converge on the correct answer. Humans also struggle to reason well to some things beyond their understanding though. LLMs can very well give their reasoning and steps and understanding for some things but not other things. Why isn't your response to this not that we just haven't taught LLMs the other things well enough yet and that we will probably get there soon enough? Would it be that surprising for GPT-5 to be able to show all of its mathematical reasoning for the question GPT-4 fails to answer now? This is all besides the point. If AI is created that outperforms humans on everything and anything by several orders of magnitude then some response along the lines of "it isn't REALLY intelligent" just sounds like either some high-falutin' semantic jostling being done by an academic divorced from real-world implications or a human drinking some serious copium wanting to still feel special for being human. I don't care how it works and that it is using processes completely different from human psychology. I care whether we can create AI in my lifetime that will outcompete me for any job I could ever hope to do. That and the totalitarian state implications of such power in the wrong hands.
chpatrick 3y ago
> This year it's the horseless carriage. Explosions in technology do happen. Just because some things were overhyped and failed doesn't mean everything hyped up will fail.
- w0de0 3y ago
  Yes but that never caught on - your premise is flawed. The polluting, antisocial, and climate effects of the car meant is was no more than a fad, popular for a few generations in the early Anthropocene before dying out. Perhaps if teleportation had not been invented in the early 2100s… IANAH.

toss1 3y ago

Yup, the AI Extinction meme is both a distraction from real harms and an effort to provoke regulations to create a moat for the big players (see famous Google memo "We Have No Moat, And Neither Does OpenAI"[0]). Most importantly, while the results of the new generative LLMs and image-processing "AIs" are impressive and sometimes useful, they are nowhere near intelligent, and have only a passing resemblance to reality. There is zero ability to actually abstract and wield concepts, nevermind conceive of and seek a goal. Fun-house mirrors of human input are not any kind of existential threat to humanity or to life on earth. However the distortions they create can amplify certain human actions, particularly disruptive actions, and distracting from managing those harms is a problem. [0] https://www.semianalysis.com/p/google-we-have-no-moat-and-neither https://www.semianalysis.com/p/google-we-have-no-moat-and-ne...

gmerc 3y ago
While I’m sharing your assessment of the motivation I do not think it’s great to take a snapshot in time on an exponential curve and argue ‘it’s far away from being intelligent’ When something goes from not being able to do something to almost human level, arguing that almost isn’t a threat is not exactly wise.
- LatteLazy 3y ago
  Of course a (flat) linear line looks very similar to an exponential early in on the curve... But I suppose that cuts both ways :)
- toss1 3y ago
  >>When something goes from not being able to do something to almost human level Point taken, and yes I have read Bostron's book and others, so I understand the runaway concern. However, the issue I have is with the "almost human level". We must look at the mechanics of what is happening. The technologies of mirrors, lenses, or photography have been able for centuries to create images at far beyond the level of most humans. Yet, capturing the vectors of incident photons is in no way reproducing human capability. These "AI" tools are capturing and reproducing the vectors of existing human output of words and/or images. The output can be impressive in both the parlor game and useful senses. Yet, there is deeply no "there" there. Just look at the "single banana problem", or the massive confident hallucination problems. Consider the responses of taking a Polaroid instant-photo camera to a pre-industrial society with sophisticated artistic capabilities. They'd at first regard the camera/printer with astonishment and consider that it may have artificially human capabilities. But they'd soon figure out that the camera has no concept of a person, and cannot compose one image of two people present only at different times. We are very much like that society regarding the camera-printer, and we're still in the astonished "Holy Cowabunga!" moment. But, the more I use it, the more I'm convinced that this is, like a camera in many situations, an occasionally extremely useful tool, but nowhere near any level of actual intelligence.
rafaelero 3y ago
> Most importantly, while the results of the new generative LLMs and image-processing "AIs" are impressive and sometimes useful, they are nowhere near intelligent, and have only a passing resemblance to reality. There is zero ability to actually abstract and wield concepts, nevermind conceive of and seek a goal. Fun-house mirrors of human input are not any kind of existential threat to humanity or to life on earth. I am no doomer but such position is utterly ignorant. GPT-4 can do plenty of complex cognitive tasks; hell, it can even do regression if you give it a bunch of data. If you think that's not intelligence then I don't think we humans are intelligent either.
- toss1 3y ago
  The question is HOW is it appearing to do regression or other math? Is it abstracting the meaning and context from the data and then performing an analysis, or just spitting out something resembling other training data it has seen after something resembling your prompts? This is easy to demonstrate with simple arithmetic. Ask ChatGPT4 what is 5 times 7? ChatGPT The product of 5 multiplied by 7 is 35. Now ask it what is 19748312 times 12347123? ChatGPT The product of 19,748,312 multiplied by 12,347,123 is 243,602,945,733,776. This is wrong; it is 243,834,837,306,376 The LLM has zero understanding of the problem, and it is not doing the math; it merely reflects back at us the closest vectors in the training set. It is no more doing your regression problems than it is doing the math here. And no, I cannot do that multiplication in my head either, but I can understand the terms, and either do the longhand arithmetic or put it into a calculator. Similarly, the human who knows how to do the regression UNDERSTANDS THE PROBLEM and applies a calculation method. The bullshitting human just spits back a plausible answer, which is what you are seeing from your LLM. What is ignorant is mistaking a parlor game, admittedly very sophisticated and often useful, for intelligence. And I do find it quite useful myself, but I do not mistake the output for something it is not. Edit: fix the asterisk times sign interpreted as formatting
  - DirkH 3y ago
    I'm not convinced human intellect isn't doing a similar thing with math when we are doing it fast. When I solve an arithmetic thing in my head I actually am not understanding or going by "the steps." I've just seen it so many times I have a kind of "sixth sense" so to speak. I.e. I'm kinda just pattern matching in the vector space of my memories. When I do this am I no longer using my intelligence? When we do math mistakes it is a form of hallucination just like for the LLM. In such instances you can ask a human to show their work and go step-by-step in which case they are less likely to "hallucinate." Do the same with an LLM and likewise you'll get a better answer as expected. In your example though it is true you're unlikely to get a LLM to converge on the correct answer. Humans also struggle to reason well to some things beyond their understanding though. LLMs can very well give their reasoning and steps and understanding for some things but not other things. Why isn't your response to this not that we just haven't taught LLMs the other things well enough yet and that we will probably get there soon enough? Would it be that surprising for GPT-5 to be able to show all of its mathematical reasoning for the question GPT-4 fails to answer now? This is all besides the point. If AI is created that outperforms humans on everything and anything by several orders of magnitude then some response along the lines of "it isn't REALLY intelligent" just sounds like either some high-falutin' semantic jostling being done by an academic divorced from real-world implications or a human drinking some serious copium wanting to still feel special for being human. I don't care how it works and that it is using processes completely different from human psychology. I care whether we can create AI in my lifetime that will outcompete me for any job I could ever hope to do. That and the totalitarian state implications of such power in the wrong hands.

chpatrick 3y ago

> This year it's the horseless carriage. Explosions in technology do happen. Just because some things were overhyped and failed doesn't mean everything hyped up will fail.

w0de0 3y ago
Yes but that never caught on - your premise is flawed. The polluting, antisocial, and climate effects of the car meant is was no more than a fad, popular for a few generations in the early Anthropocene before dying out. Perhaps if teleportation had not been invented in the early 2100s… IANAH.